Research Scientist, Robot Foundation Models
$370k - $513k • Sunnyvale, California USA • Full-time
Posted 28d ago
Job Location
Sunnyvale, California USA
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Research Engineer
About the job
Wayve is seeking a founding Research Scientist to join the Multi-Embodiment Generalist Agent (MEGA) team. This role focuses on building foundation models for general-purpose robots beyond self-driving vehicles, creating intelligent agents capable of perceiving, reasoning, moving, and manipulating the physical world across diverse embodiments. You will play a senior, high-impact role in defining the research agenda, technical strategy, and foundations of a new robotics program. The work involves the entire robot-learning stack, from scalable data flywheels and new model architectures to training large models, designing evaluations, and deploying policies on real robots. You will collaborate with researchers, ML engineers, and roboticists to advance ambitious ideas from research hypotheses to large-scale experiments and real-world capabilities.
Responsibilities
- Conduct research in architectures and data for robot foundation models.
- Implement and experiment with various models like VLAs, WAMs, omni models, and video models.
- Implement and experiment with learning approaches such as reinforcement learning (RL) and behavioral cloning (BC).
- Synthesize and filter large video datasets for model training and evaluation.
- Build scalable distributed training pipelines and infrastructure for large models and datasets.
- Influence and/or own robot policy development, data strategy, and model design decisions.
- Collaborate with scientists, engineers, and robotics teams to connect research progress to real-world robot performance.
- Communicate research findings internally and contribute to external publications.
Requirements
- Deep experience in machine learning, with a focus on vision-language models, video models, robot policies, or foundation models for robotics/embodied AI.
- Experience with scalable training, including multi-node training, large datasets, and/or large model training.
- Strong research track record with publications in top-tier venues (e.g., ICRA, CoRL, CVPR, NeurIPS, ICML, ICLR).
- Strong coding skills and hands-on experience with modern machine learning frameworks.
- Ability to design and drive an independent research agenda while collaborating with engineering and robotics teams.
- Experience translating research ideas into working systems, experiments, or deployed capabilities.
- Strong communication skills and ability to influence technical direction across teams.